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WO1997037336A1 - Systeme de detection d'avion - Google Patents

Systeme de detection d'avion Download PDF

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Publication number
WO1997037336A1
WO1997037336A1 PCT/AU1997/000198 AU9700198W WO9737336A1 WO 1997037336 A1 WO1997037336 A1 WO 1997037336A1 AU 9700198 W AU9700198 W AU 9700198W WO 9737336 A1 WO9737336 A1 WO 9737336A1
Authority
WO
WIPO (PCT)
Prior art keywords
image
aircraft
object detection
image acquisition
camera
Prior art date
Application number
PCT/AU1997/000198
Other languages
English (en)
Inventor
Glen William Auty
Michael John Best
Timothy John Davis
Ashley John Dreier
Ian Barry Macintyre
Original Assignee
Commonwealth Scientific And Industrial Research Organisation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Commonwealth Scientific And Industrial Research Organisation filed Critical Commonwealth Scientific And Industrial Research Organisation
Priority to EP97913985A priority Critical patent/EP0890161A4/fr
Priority to NZ332051A priority patent/NZ332051A/xx
Priority to AU21438/97A priority patent/AU720315B2/en
Publication of WO1997037336A1 publication Critical patent/WO1997037336A1/fr

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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft
    • G08G5/20—Arrangements for acquiring, generating, sharing or displaying traffic information
    • G08G5/22—Arrangements for acquiring, generating, sharing or displaying traffic information located on the ground
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64F—GROUND OR AIRCRAFT-CARRIER-DECK INSTALLATIONS SPECIALLY ADAPTED FOR USE IN CONNECTION WITH AIRCRAFT; DESIGNING, MANUFACTURING, ASSEMBLING, CLEANING, MAINTAINING OR REPAIRING AIRCRAFT, NOT OTHERWISE PROVIDED FOR; HANDLING, TRANSPORTING, TESTING OR INSPECTING AIRCRAFT COMPONENTS, NOT OTHERWISE PROVIDED FOR
    • B64F1/00—Ground or aircraft-carrier-deck installations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64F—GROUND OR AIRCRAFT-CARRIER-DECK INSTALLATIONS SPECIALLY ADAPTED FOR USE IN CONNECTION WITH AIRCRAFT; DESIGNING, MANUFACTURING, ASSEMBLING, CLEANING, MAINTAINING OR REPAIRING AIRCRAFT, NOT OTHERWISE PROVIDED FOR; HANDLING, TRANSPORTING, TESTING OR INSPECTING AIRCRAFT COMPONENTS, NOT OTHERWISE PROVIDED FOR
    • B64F1/00—Ground or aircraft-carrier-deck installations
    • B64F1/002—Taxiing aids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/254—Analysis of motion involving subtraction of images
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/255—Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft
    • G08G5/70—Arrangements for monitoring traffic-related situations or conditions
    • G08G5/72—Arrangements for monitoring traffic-related situations or conditions for monitoring traffic
    • G08G5/727—Arrangements for monitoring traffic-related situations or conditions for monitoring traffic from a ground station
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section

Definitions

  • the present invention relates to an object detection system and, in particular to an aircraft detection system.
  • the International Civil Aviation Organization (ICAO) has established regulations which require all civil aircraft to have registration markings beneath the port wing to identify an aircraft.
  • the markings denote the nationality of an aircraft and its registration code granted by the ICAO.
  • airline operators do not follow the regulations and the markings appear on an aircraft's fuselage.
  • Owners of aircraft are charged for airport use, but a satisfactory system has not been developed to automatically detect aircraft and then, if necessary, administer a charge to the owner.
  • Microwave signals for detecting an aircraft can interfere with microwave frequencies used for airport communications and, similarly, radar signals can interfere with those used for aircraft guidance systems.
  • a system which can be used to detect an aircraft using unobtrusive passive technology is desired.
  • an object detection system including :
  • passive sensing means for receiving electromagnetic radiation from a moving object and generating intensity signals representative of the received radiation, and processing means for subtracting said intensity signals to obtain a differential signature representative of the position of said moving object.
  • the present invention also provides an image acquisition system including : at least one camera for acquiring an image of at least part of a moving object, in response to a trigger signal, and analysis means for processing said image to locate a region in said image including markings identifying said object and processing said region to extract said markings for a recognition process.
  • the present invention also provides an object detection method including: passively sensing electromagnetic radiation received from a moving object; generating intensity signals representative of the received radiation; and subtracting said intensity signals to obtain a differential signature representative of the position of said moving object.
  • the present invention also provides an image acquisition method including: acquiring an image of at least part of a moving object, in response to a trigger signal, using at least one camera, and
  • processing said image to locate a region in said image including markings identifying said object and processing said region to extract said markings for a recognition process.
  • Figure 1 is a block diagram of a preferred embodiment of an aircraft detection system
  • Figure 2 is a schematic diagram of a preferred embodiment of the aircraft detection system
  • Figure 3 is a block diagram of a connection arrangement for components of the aircraft detection system
  • Figure 4 is a more detailed block diagram oi a proximity detector and a tracking system for the aircraft detection system
  • Figure 5 is a coordinate system used for the proximity detector
  • Figures 6(a) and 6(b) are underneath views of discs of sensors of the tracking system
  • Figure 7 is a schematic diagram of an image obtained by the tracking system
  • Figures 8 and 9 are images obtained from a first embodiment of the tracking system
  • Figure 10 is a graph of a pixel row sum profile for an image obtained by the tracking system
  • Figure 11 is a graph of a difference profile obtained by subtracting successive row sum profiles
  • Figure 12 is a diagram of a coordinate system for images obtained by the tracking system
  • Figure 13 is a diagram of a coordinate system for the aircraft used for geometric correction of the images obtained by the tracking system
  • Figure 14 is a diagram of a coordinate system used for predicting a time to generate an acquisition signal
  • Figure 15 is a graph of aircraft position in images obtained by the tracking system over successive frames
  • Figure 16 is a graph of predicted trigger frame number over successive image frames obtained by the tracking system
  • Figure 17 is a schematic diagram of a pyroelectric sensor used in a second embodiment of the tracking system.
  • Figure 18 is graphs of differential signatures obtained using the second embodiment of the tracking system.
  • Figures 19 and 20 are images obtained of an aircraft by high resolution cameras of an acquisition system of the aircraft detection system
  • Figure 21 is a schematic diagram of an optical sensor system used for exposure control of the acquisition cameras
  • Figure 22 is a flow diagram of a preferred character location process executed on image data obtained by the high resolution cameras
  • Figure 23 is a diagram of images produced during the character location process.
  • Figure 24 is a flow diagram of a character recognition process executed on a binary image of the characters extracted from an image obtained by one of the high resolution cameras.
  • An aircraft detection system 2 as shown in Figure 1 , includes a proximity detector 4, a tracking sensor system 6, an image processing system 8, an image acquisition system 10 and an analysis system 12.
  • a control system 14 can be included to control the image acquisition system 10 on the basis of signals provided by the image processing system 8, and also control an illumination unit 16.
  • the proximity detector 4 and the tracking sensor system 6 includes sensors 3 which may be placed on or near an aircraft runway 5 to detect the presence of an aircraft 28 using visual or thermal imaging or aural sensing techniques Also located on or near the runway 5 is at least one high resolution camera 7 of the image acquisition system 10.
  • the sensors 3 and the acquisition camera 7 are connected by data and power lines 9 to an instrument rack 11 , as shown in Figure 2, which may be located adjacent or near the runway 5.
  • the instrument rack 11 may alternatively be powered by its own independent supply which may be charged by solar power
  • the instrument rack 11 includes control circuitry and image processing circuitry which is able to control activation of the sensors 3 and the camera 7 and perform image processing, as required.
  • the instrument rack 11 , the data and power lines 9, the sensors 3 and the acquisition camera 7 can be considered to form a runway module which may be located at the end of each runway of an airport.
  • a runway module can be connected back to a central control system 13 using an optical fibre or other data link 15 Images provided by the sensors 3 may be processed and passed to the central system 13 for further processing, and the central system 13 would control triggering of the acquisition cameras 7. Alternatively image processing for determining triggering of the acquisition camera 7 may be performed by each instrument rack 11 .
  • the central control system 13 includes the analysis system 12. One method of configuring connection of the instrument racks 11 to the central control system 13 is illustrated in Figure 3.
  • the optical fibre link 15 may include dedicated optical fibres 17 for transmitting video signals to the central control system 13 and other optical fibres 19 dedicated to transmitting data to and receiving data from the central control system 13 using the Ethernet protocol or direct serial data communication .
  • a number of different alternatives can be used for connecting the runway modules to the central control system 13.
  • the runway modules and the control system 13 may be connected as a Wide Area Network (WAN) using Asynchronous Transfer Mode (ATM) or Synchronous Digital Hierarchy (SDH) links.
  • the runway modules and the central control system 13 may also be connected as a Local Area Network (LAN) using a LAN protocol, such as Ethernet Physical connections may be made between the runway modules and the central control system 13 or alternatively wireless transmission techniques may be used, such as using infrared or microwave signals for communication.
  • WAN Wide Area Network
  • ATM Asynchronous Transfer Mode
  • SDH Synchronous Digital Hierarchy
  • the runway modules and the central control system 13 may also be connected as a Local Area Network (LAN) using a LAN protocol, such as Ethernet Physical connections
  • the proximity detector 4 determines when an aircraft is within a predetermined region, and then on detecting the presence of an aircraft activates the tracking sensor system 6.
  • the proximity detector 4, as shown in Figure 4, may include one or more pyroelectnc devices 21 , judiciously located at an airport, and a signal processing unit 23 and trigger unit 25 connected thereto in order to generate an activation signal to the tracking sensor system 6 when the thermal emission of an approaching aircraft exceeds a predetermined threshold.
  • the proximity detector 4 may use one or more pyroelectnc point sensors that detect the infrared radiation emitted from the aircraft 28.
  • a mirror system can be employed with a point sensor 70 to enhance its sensitivity to the motion of the aircraft 28.
  • the point sensor 70 may consist of two or more pyroelectric sensors configured in a geometry and with appropriate electrical connections so as to be insensitive to the background infrared radiation and slowly moving objects. With these sensors the rate of motion of the image of the aircraft 28 across the sensor 70 is important.
  • the focal length of the mirror 72 is chosen to optimise the motion of the image across the sensor 70 at the time of detection. As an example, if the aircraft at altitude H with glide slope angle ⁇ GS moves with velocity V and passes overhead at time t o , as shown in Figure 5, then the position h of the image of the aircraft 28 on the sensor 70 is
  • the proximity detector 4 may include different angled point sensors to determine when an aircraft enters the monitored region and is about to land or take-off In response to the activation signal, the tracking sensor system 6 exposes the sensor 3 to track the aircraft. Use of the proximity detector 4 allows the sensor 3 to be sealed in a housing when not in use and protected from damaging environmental conditions, such as hailstorms and blizzards or fuel.
  • the sensor 3 is only exposed to the environment for a short duration whilst an aircraft is in the vicinity of the sensor 3. If the tracking system 6 is used in conditions where the sensor 3 can be permanently exposed to the environment or the sensor 3 can resist the operating conditions, then the proximity detector 4 may not be required.
  • the activation signal generated by the proximity detector 4 can also be used to cause the instrument rack 11 and the central control system 13 to adjust the bandwidth allocated on the link 15 so as to provide an adequate data transfer rate for transmission of video signals from the runway module to the central system 13. If the bandwidth is fixed at an acceptable rate or the system 2 only uses local area network communications and only requires a reduced bandwidth, then again the proximity detector 4 may not be required.
  • the tracking sensor system 6 includes one or more tracking or detection cameras 3 which obtain images of an aircraft as it approaches or leaves a runway. From a simple image of the aircraft, aspect ratios, such as the ratio of the wingspan to the fuselage length can be obtained.
  • the tracking camera 3 used is a thermal camera which monitors thermal radiation received in the 10 to 14 ⁇ m wavelength range and is not dependent on lighting conditions for satisfactory operation. Use of the thermal cameras is also advantageous as distribution of temperatures over the observed surfaces of an aircraft can be obtained, together with signatures of engine exhaust emissions and features in the fuselage or engines.
  • the tracking camera 3 can obtain an instantaneous two-dimensional image l n using all of the sensors in a CCD array of the camera, or alternatively one row of the array perpendicular to the direction of motion of the aircraft can be used to obtain a linear image at each scan and the linear image is then used to build up a two-dimensional image l n for subsequent processing .
  • a rotating disc system is employed.
  • the use of a rotating disc for removing water drops from windows is used on marine vessels.
  • a reflective or transparent disc is rotated at high speed in front of the window that is to be kept clear. Water droplets falling on the disk experience a large shear force related to the rotation velocity. The shear force is sufficient to atomise the water drop, thereby removing it from the surface of the disc.
  • a transparent disc of approximate diameter 200 mm is mounted to an electric motor and rotated to a frequency of 60 Hz.
  • a camera with a 4 8 mm focal length lens was placed below a glass window which in turn was beneath the rotating disc.
  • the results of inserting the rotating disc are illustrated in Figure 6(a), which shows the surface of a camera housing without the rotating disc, and in Figure 6(b), which shows the surface of a camera housing with the rotating disc activated and in rain conditions.
  • the image processing system 8 processes the digital images provided by the tracking sensor system 6 so as to extract in real-time information concerning the features and movement of the aircraft.
  • the images provided to the image processing system depending on the tracking cameras employed, provide an underneath view of the aircraft, as shown in Figure 7.
  • the tips of the wings or wingspan points 18 of the aircraft are tracked by the image processor system 8 to determine when the image acquisition system 10 should be activated so as to obtain the best image of the registration markings on the port wing 20 of the aircraft.
  • the image processing system 8 generates an acquisition signal using a trigger logic circuit 39 to trigger the camera of the image acquisition system 10.
  • the image processing system 8 also determines and stores data concerning the wingspan 22 of the aircraft and other details concerning the size, shape and ICAO category (A to G) of the aircraft.
  • the image processing system 8 classifies the aircraft on the basis of the size which can be used subsequently when determining the registration markings on the port wing 20.
  • the data obtained can also be used for evaluation of the aircraft during landing and/or take-off.
  • a pyroelectnc sensor 27 can be used with a signal processing wing detection unit 29 to provide a tracking system 1 which also generates the acquisition signal using the trigger logic circuit 39, as shown in Figure 4 and described later.
  • Detecting moving aircraft in the field of view of the sensor 3 or 27 is based on forming a profile or signature of the aircraft, P(y,t), that depends on a spatial coordinatey and time t .
  • a difference profile ⁇ P(y,t) is formed.
  • the profile or signature can be differenced in time or in space because these differences are equivalent for moving objects. If the intensity of the light or thermal radiation from the object is not changing then the time derivative of the profile obtained from this radiation is zero.
  • a time derivative of a moving field can be written as a convective derivative involving partial derivatives, which gives the equation where v is the speed of the object as observed in the profile.
  • the profile can be differenced in space ⁇ y P(y,t) . Then an extremum in the profile P(y, t) will correspond to a point where the difference profile ⁇ y P(y, t) crosses zero.
  • a profile P(y,t) is formed and a difference profile ⁇ t P(y,t) is obtained by differencing in time, as described below. According to equation (4) this is equivalent to a profile of a moving object that is differenced in space. Therefore the position y p of the zero crossing point of A f P(y,t) at time t is also the position of the zero crossing point of ⁇ y P(y,t) which locates an extremum in P(y,r) .
  • the difference between the radiation received by a sensor 27 from two points in space is obtained as a function of time, ⁇ y S(t) , as described below. If there are no moving features in the field of view, then the difference is constant. If any object in the field of view is moving, then the position of a point on the object is related to time using equation (5). This allows a profile or signature differenced in space to be constructed
  • a y P(y(t),t) ⁇ y S(t) (6) and, as described above, allows an extremum corresponding to an aircraft wing to be located in the profile from the zero crossing point in the differential signature.
  • the image acquisition system 10 includes at least one high resolution camera
  • the illumination unit 16 is also triggered simultaneously to provide illumination of the aircraft during adverse lighting conditions, such as at night or during inclement weather.
  • the acquired images are passed to the analysis system 12 which performs Optical Character Recognition (OCR) on the images to obtain the registration code.
  • OCR Optical Character Recognition
  • the registration code corresponds to aircraft type and therefore the aircraft classification determined by the image processing system 8 can be used to assist to the recognition process, particularly when characters of the code are obscured in an acquired image.
  • the registration code extracted and any other information concerning the aircraft can be then passed to other systems via a network connection 24.
  • the tracking system 1 is activated by the proximity detector 4.
  • the proximity detector 4 is usually the first stage detection system to determine when the aircraft is in the proximity of the more precise tracking system 1.
  • the tracking system 1 includes the tracking sensor system 6 and the image processing system 8 and according to one embodiment the images from the detection cameras 3 of the sensor system 6 are used by the image processing system 8 to provide a trigger for the image acquisition system when some point in the image of the aircraft reaches a predetermined pixel position.
  • One or more detection cameras 3 are placed in appropriate locations near the airport runway such that the aircraft passes within the field of view of the cameras 3.
  • a tracking camera 3 provides a sequence of images, ⁇ l n ⁇ .
  • the image processing system 8 subtracts a background image from each image l n of the sequence.
  • the background image represents an average of a number of preceding images. This yields an image ⁇ l n that contains only those objects that have moved during the time interval between images.
  • the image ⁇ l n is thresholded at appropriate values to yield a binary image, i.e. one that contains only two levels of brightness, such that the pixels comprising the edges of the aircraft are clearly distinguishable.
  • the pixels at the extremes of the aircraft in the direction perpendicular to the motion of the aircraft will correspond to the edges 18 of the wings of the aircraft.
  • Imaging the aircraft using thermal infrared wavelengths and detecting the aircraft by its thermal radiation renders the aircraft self-luminous so that it can be imaged both during the day and night primarily without supplementary illumination
  • Infrared (IR) detectors are classified as either photon detectors (termed cooled sensors herein), or thermal detectors (termed uncooled sensors herein).
  • Photon detectors photoconductors or photodiodes
  • Photon detectors produce an electrical response directly as the result of absorbing IR radiation. These detectors are very sensitive, but are subject to noise due to ambient operating temperatures. It is usually necessary to cryogenically cool (80°K) these detectors to maintain high sensitivity.
  • Thermal detectors experience a temperature change when they absorb IR radiation, and an electrical response results from temperature dependence of the material property. Thermal detectors are not generally as sensitive as photon detectors, but perform well at room temperature.
  • the cooled sensing devices are formed from Mercury Cadmium Tellunde offer far greater sensitivity than uncooled devices, which may be formed from Barium Strontium Titanate. Their Net Equivalent Temperature Difference (NETD) is also superior.
  • NETD Net Equivalent Temperature Difference
  • uncooled sensor a chopper can be used to provide temporal modulation of the scene. This permits AC coupling of the output of each pixel to remove the average background. This minimises the dynamic range requirements for the processing electronics and amplifies only the temperature differences. This is an advantage for resolving differences between cloud, the sun, the aircraft and the background.
  • the advantage of differentiation between objects is that it reduced the load on subsequent image processing tasks for segmenting the aircraft from the background and other moving objects such as the clouds.
  • Both a cooled and uncooled thermal infrared imaging system 6 has been used during day, night and foggy conditions.
  • the system 6 produced consistent images of the aircraft in all these conditions, as shown in Figures 8 and 9.
  • the sun in the field of view produced no saturation artefacts or flaring in the lens.
  • the image processing system 8 uses a background subtraction method in an attempt to eliminate slowly moving or stationary objects from the image, leaving only the fast moving objects. This is achieved by maintaining a background image that is updated after a certain time interval elapses. The update is an incremental one based on the difference between the current image and the background.
  • the incremental change is such that the background image can adapt to small intensity variations in the scene but takes some time to respond to large variations.
  • the background image is subtracted from the current image, a modulus is taken and a threshold applied.
  • the result is a binary image containing only those differences from the background that exceed the threshold.
  • Equation (7) shows that the value of this difference depends on the velocity v of the feature at (x,y) and the intensity gradient.
  • B(x,y,t) 1 if a feature is located at (x,y) at time t
  • B(x,y,t) Orepresents the background.
  • the fast moving features belong to the aircraft.
  • the two-dimensional binary image can be compressed into one dimension by summing along each pixel row of the binary image,
  • Equation (9) demonstrates an obvious fact that the time derivative of a profile gives information on the changes (such as motion) of feature A only when the changes in A do not overlap features C
  • C(x,y,t) must cover as small an area as possible
  • the time difference between profiles gives the motion of the aircraft.
  • the difference profile corresponding to Figure 10 is shown in Figure 11 where the slow moving clouds have been eliminated. The wing positions occur at the zero-crossing points 33 and 34 Note that the clouds have been removed, apart from small error terms.
  • the method is implemented using a programmable logic circuit of the image processing system 8 which is programmed to perform the row sums on the binary image and to output these as a set of integers after each video field.
  • a programmable logic circuit of the image processing system 8 which is programmed to perform the row sums on the binary image and to output these as a set of integers after each video field.
  • the difference profile is analysed to locate valid zero crossing points corresponding to the aircraft wing positions
  • a valid zero crossing is one in which the difference profile initially rises above a threshold l ⁇ for a minimum distance y ⁇ and falls through zero to below -l ⁇ for a minimum distance y ⁇ .
  • the magnitude of the threshold l ⁇ is chosen to be greater than the error term ⁇ (C) which is done to discount the affect produced by slow moving features, such as clouds.
  • the peak value of the profile corresponding to the aircraft wing, can be obtained by summing the difference values when they are valid up to the zero crossing point. This method removes the contributions to the peak from the non- overlapping clouds It can be used as a guide to the wing span of the aircraft.
  • the changes in position of the aircraft in the row-sum profile are used to determine a velocity for the aircraft that can be used for determining the image acquisition or trigger time, even if the aircraft is not in view. This situation may occur if the aircraft image moves into a region on the sensor that is saturated, or if the trigger point is not in the field of view of the camera 3.
  • geometric corrections to the aircraft position are required to account for the distortions in the image introduced by the camera lens.
  • a normalised variable Z N ZIY o can be used If y o is the coordinate of the centre of the images, f is the focal length of the lens and ⁇ c is the angle of the camera from the horizontal in the vertical plane, then where the tangent has been expanded using a standard trigonometric identity. Using (10) and (11) an expression for the normalised distance Z N is obtained
  • a length X on it in the X direction subtends an angle in the horizontal plane of
  • the x coordinate is corrected to a value at y 1 . Since X N should be independent of position, then a length x 2 - x 0 at y 2 has a geometrically corrected length of
  • ⁇ 1/f is chosen so that x and y are measured in terms of pixel numbers. If y 0 is the centre of the camera centre and it is equal to half the total number of pixels, and if ⁇ FOV is the vertical field of view of the camera, then )
  • This relation allows ⁇ to be calculated without knowing the lens focal length and the dimensions of the sensor pixels.
  • the aircraft will cross the trigger point located at y ⁇ at a time t ⁇ estimated by )
  • the method is able to predict the time for triggering the acquisition system 10 based on observations of the position of the aircraft 28.
  • a set of coordinates are defined such that the axis points vertically upwards, the axis points horizontally along the runway towards the approaching aircraft, and p is horizontal and perpendicular to the runway.
  • the image 66 of the aircraft is located in the digitised image by pixel values (x p ,y p ) , where x p is defined to be the vertical pixel value and y the horizontal value.
  • the lens on the camera inverts the image so that a light ray from the aircraft strikes the sensor at position (-x p' -y p, 0) , where the sensor is located at the coordinate origin.
  • Figure 14 shows a ray 68 from an object, such as a point on the aircraft, passing through a lens of a focal length f , and striking the imaging sensor at a point (-x p' -y p ) , where x p and y p are the pixel values.
  • the equation locating a point on the ray is given by
  • z is the horizontal distance along the ray
  • subscript c refers to the camera coordinates.
  • the camera axis c is collinear with the lens optical axis. It will be assumed that z/f»1 , which is usually the case.
  • z(t) is the horizontal position of the aircraft at time t
  • ⁇ GS is the glide-slope angle
  • the aim is to determine f 0 from a series of values of z p (t) at t determined from the image of the aircraft.
  • the trigger time, t o can be expressed in terms of the parameters a, b and c
  • equation (34) is a prediction of the relationship between the measured values x p and t , based on a simple model of the optical system of the detection camera 3 and the trajectory of the aircraft 28.
  • the parameters a, b and c are to be chosen so as to minimise the error of the model fit to the data, i.e. make equation (34) be as close to zero as possible.
  • x n be the location of the aircraft in the image, i.e. pixel value, obtained at time t n .
  • the chi-square statistic is for N pairs of data points.
  • the optimum values of the parameters are those that minimise the chi-square statistic, i.e. those that satisfy equation (34).
  • a graph of aircraft image position as a function of image frame number is shown in Figure 15.
  • the predicted point 70 is shown in Figure 16 as a function of frame number.
  • the aircraft can be out of the view of the camera 3 for up to 1.4 seconds and the system 2 can still trigger the acquisition camera 7 to within 40 milliseconds of the correct time. For an aircraft travelling at 62.5 m/s, the system 2 captures the aircraft to within 2.5 metres of the required position.
  • the tracking system 6, 8 may also use an Area-Parameter Accelerator (APA) digital processing unit, as discussed in International Publication No. WO 93/19441 , to extract additional information, such as the aspect ratio of the wing span to the fuselage length of the aircraft and the location of the centre of the aircraft.
  • APA Area-Parameter Accelerator
  • the tracking system 1 can also be implemented using one or more pyroelectric sensors 27 with a signal processing wing detection unit 29.
  • Each sensor 27 has two adjacent pyroelectric sensing elements 40 and 42, as shown in Figure 17, which are electrically connected so as to cancel identical signals generated by each element.
  • a plate 44 with a slit 46 is placed above the sensing elements 40 and 42 so as to provide the elements 40 and 42 with different fields of view 48 and 50.
  • the fields of view 48 and 50 are significantly narrower than the field of view of a detection camera discussed previously If aircraft move above the runway in the direction indicated by the arrow 48, the first element 40 has a front field of view 48 and the second element 42 has a rear field of view 50.
  • the first element 40 detects the thermal radiation of the aircraft before the second element 42, the aircraft 28 will then be momentarily in both fields of view 48 and 50, and then only detectable by the second element 42.
  • An example of the difference signals generated by two sensors 27 is illustrated in Figure 18 where the graph 52 is for a sensor 27 which has a field of view that is directed at 90° to the horizontal and a sensor 27 which is directed at 75° to the horizontal.
  • Graph 54 is an expanded view of the centre of graph 52. The zero crossing points of peaks 56 in the graphs 52 and 54 correspond to the point at which the aircraft 28 passes the sensor 27.
  • a time can be determined for generating an acquisition signal to trigger the high resolution acquisition cameras 7.
  • the speed can be determined from movement of the zero crossing points over time, in a similar manner to that described previously.
  • the image acquisition system 10 acquires an image of the aircraft with sufficient resolution for the aircraft registration characters to be obtained using optical character recognition.
  • the system 10 includes two high resolution cameras 7 each comprising a lens and a CCD detector array. Respective images obtained by the two cameras 7 are shown in Figures 19 and 20.
  • the minimum pixel dimension and the focal length of the lens determine the spatial resolution in the image. If the dimension of a pixel is L p , the focal length f and the altitude of the aircraft is h, then the dimension of a feature W min on the aircraft that is mapped onto a pixel is
  • the character recognition process used requires each character stroke to be mapped onto at least four pixels with contrast levels having at least 10% difference from the background.
  • the width of a character stroke in the aircraft registration is regulated by the ICAO.
  • the field of view of the system 10 at altitude h is determined by the spatial resolution W min chosen at altitude h max and the number of pixels N pl along the length of the CCD,
  • the image moves a distance less than the size of a pixel during the exposure. If the aircraft velocity is v, then the time to move a distance equal to the required spatial resolution W min is
  • W min 0 02 m
  • the exposure time to avoid excessive blurring is t ⁇ 240 ⁇ s.
  • the focal length of the lens in the system 10 can be chosen to obtain the required spatial resolution at the maximum altitude This fixes the field of view.
  • the field of view may be varied by altering the focal length according to the altitude of the aircraft
  • the range of focal lengths required can be calculated from equation (44).
  • the aircraft registration during daylight conditions, is illuminated by sunlight or scattered light reflected from the ground .
  • the aircraft scatters the light that is incident, some of which is captured by the lens of the imaging system
  • the considerable amount of light reflected from aluminium fuselages of an aircraft can affect the image obtained, and is taken into account
  • the light power falling onto a pixel of the CCD is given by *
  • L ⁇ is the solar spectral radiance
  • ⁇ is the wavelength bandpass of the entire configuration
  • ⁇ sun is the solid angle subtended by the sun
  • R gnd is the reflectivity of the ground
  • P A is the reflectivity of the aircraft
  • a p is the area of a pixel in the CCD detector
  • f# is the lens f-number.
  • the solar spectral radiance L ⁇ varies markedly with wavelength ⁇ .
  • the power falling on a pixel will therefore vary over a large range. This can be limited by restricting the wavelength range ⁇ passing to the sensor and optimally choosing the centre wavelength of this range.
  • the optimum range and centre wavelength are chosen to match the characteristics of the imaging sensor.
  • the optimum wavelength range and centre wavelength are chosen in the near infrared waveband, 0. 69 to 2.0 microns. This limits the variation in light power on a pixel in the sensor to within the useable limits of the sensor.
  • a KODAKTM KAF-1600L imaging sensor (a monolithic silicon sensor with lateral overflow anti-blooming) was chosen that incorporated a mechanism to accommodate a thousandfold saturation of each pixel, giving a total acceptable range of light powers in each pixel of 10 5 . This enables the sensor to produce a useful image of an aircraft when very bright light sources, for example the sun, are in its field of view.
  • the correct choice of sensor and the correct choice of wavelength range and centre wavelength enables an image to be obtained within a time interval that arrests the motion of the aircraft and that provides an image with sufficient contrast on the aircraft registration to enable digital image processing and recognition of the registration characters.
  • the optimum wavelength range was therefore set to between 0.69 ⁇ m and 2.0 ⁇ m.
  • the CCD sensor and system electronics are chosen to accommodate this range of light powers.
  • the aircraft registration requires additional illumination from the illumination unit 16.
  • the light source of the unit 16 needs to be sufficient to illuminate the aircraft at its maximum altitude. If the source is designed to emit light into a solid angle that just covers the field of view of the imaging system then the light power incident onto a pixel of the imaging system 10 due to light emitted from the source and reflected from the aircraft is given by where A A is the area on the aircraft imaged onto a pixel of area A p , P s is the light power of the source, P A is the aircraft reflectivity, N ptot is the total number of pixels in the CCD sensor and f# is the f-number of the lens.
  • the aperture of the lens on the acquisition camera 7 is automatically adjusted to control the amount of light on the imaging sensor in order to optimise the image quality for digital processing.
  • the intensity level of the registration characters relative to the underside of the aircraft needs to be maintained to provide good contrast between the two for OCR.
  • the power P s of the flash 16 is automatically adjusted in accordance with the aperture setting f# of the acquisition camera 7 to optimise the image quality and maintain the relative contrast between the registration characters and the underside of the aircraft, in accordance with the relationship expressed in equation (50).
  • the aperture of the lens may be very small and the power of the flash may be increased to provide additional illumination of the underside, whereas during night conditions, the aperture may be fully opened and the power of the flash reduced considerably as additional illumination is not required.
  • the electrical gam of the electronic circuits connected to an acquisition camera 7 is adjusted automatically to optimise the image quality.
  • one or more point optical sensors 60, 62 are used to measure the ambient lighting conditions.
  • the electrical output signals of the sensors 60, 62 are processed by the acquisition system 10 to produce the information required to control the camera aperture and/or gain.
  • Two point sensors 60, 62 sensitive to the same optical spectrum as the acquisition cameras 7 can be used.
  • One sensor 60 receives light from the sky that passes through a diffusing plate 64 onto the sensor 60.
  • the diffusing plate 64 collects light from many different directions and allows it to reach the sensor 60.
  • the second sensor 62 is directed towards the ground to measure the reflected light from the ground.
  • the analysis system 12 processes the aircraft images obtained by a high resolution camera 7 according to an image processing procedure 100, as shown in Figure 22, which is divided into two parts 102 and 104.
  • the first part 102 operates on a sub-sampled image 105, as shown in Figure 23, to locate regions that contain features that may be registration characters, whereas the second part 104 executes a similar procedure but is done using the full resolution of the original image and is executed only on the regions identified by the first part 102.
  • the sub-sampled image 105 is the original image with one pixel in four removed in both row and column directions, resulting in a one in sixteen sampling ratio .
  • the first part 102 receives the sub-sampled image at step 106 and filters the image to remove features which are larger than the expected size of the registration characters (b) at step 108
  • Step 108 executes a morphological operation of linear closings applied to a set of lines angled between 0 and 180°.
  • the operation passes a kernel or window across the image 105 to extract lines which exceed a predetermined length and are at a predetermined angle .
  • the kernel or window is passed over the image a number of times and each time the predetermined angle is varied .
  • the lines extracted from all of the passes are then subtracted from the image 105 to provide a filtered difference image 109.
  • the filtered difference image 109 is then thresholded or binansed at step 110 to convert it from a grey scale image to a binary scale image 111 . This is done by setting to 1 all image values that are greater than a threshold and setting to 0 all other image values.
  • the threshold at a given point in the image is determined from a specified multiple of standard deviations from the mean calculated from the pixel values within a window centred on the given point.
  • the binansed image 111 is then filtered at step 112 to remove all features that have pixel densities in a bounding box that are smaller or larger than the expected pixel density for a bounded registration character.
  • the image 111 is then processed at step 114 to remove all features which are not clustered together like registration characters.
  • Step 114 achieves this by grouping together features that have similar sizes and that are close to one another. Groups of features that are smaller than a specified size are removed from the image to obtain a cleaned image 113. The cleaned image 113 is then used at step 116 to locate regions of interest. Regions of interest are obtained in step 116 from the location and extents of the groups remaining after step 114. Step 116 produces regions of interest which include the registration characters and areas of the regions are bounded above and below, as for the region 115 shown in Figure 23.
  • the regions of interest obtained by the first part 102 of the procedure 100 are further processed individually using the full resolution of the original image and the second part 104 of the procedure.
  • the second part 104 takes a region of interest 115 from the original image at step 120 and for that region filters out features larger than the expected character sizes at step 122, using the same morphological operation of linear closings applied to a set of lines angled between 0 and 180°, followed by image subtraction, as described above, to obtain image 117.
  • the filtered image 117 is then binansed at step 124 by selecting a filter threshold that is representative of the pixel values at the edges of features. To distinguish the registration characters from the aircraft wing or body the filter threshold needs to be set correctly.
  • a mask image of significant edges in image 117 is created by calculating edge-strengths at each point in image 117 and setting to 1 all points that have edge-strengths greater than a mask threshold and setting to 0 all other points.
  • An edge-strength is determined by taking at each point pixel gradients in two directions, ⁇ x and ⁇ y, and calculating to give the edge-strength at that point. The mask threshold at a given
  • the filter threshold for each point in image 117 is then determined from a specified multiple of standard deviations from the mean calculated from the pixel values at all points within a window centred on the given point that correspond to non-zero values in the mask image.
  • the binarised image 118 is then filtered at step 126 to remove features that are smaller than the expected character sizes.
  • Features are clustered together at step 128 that have similar sizes, that are near to one another and that are associated with similar image values in image 117.
  • step 130 the correctly clustered features that have sizes, orientations and relative positions that deviate too much from the averages for the clusters are filtered out to leave features that form linear chains.
  • step 132 if the number of features remaining in the image produced by step 130 is greater than 3, then a final image is created by rotating image 118 to align the linear chain of features with the image rows and by masking out features not belonging to the linear chain.
  • the final image is passed to a character recognition process 200 to determine whether the features are registration characters and, if so, which characters.
  • the final image undergoes a standard optical character recognition process 200, as shown in Figure 24, to generate character string data which represents the ICAO characters on the port wing.
  • the process 200 includes receiving the final image at step 202, which is produced by step 132 of the image processing procedure 100, and separating the characters of the image at step 204.
  • the size of the characters are normalised at step 206 and at step 208 correction for the alignment of the characters is made and further normalisation occurs.
  • Character features are extracted at step 210 and an attempt made to classify the features of the characters extracted at step 212
  • Character rules are applied to the classified features at step 214 so as to produce a binary string representative of the registration characters at step 216.
  • the system 2 has been described above as being one which is particularly suitable for detecting an aircraft, it should be noted that many features of the system can be used for detecting and identifying other moving objects
  • the embodiments of the tracking system 1 may be used for tracking land vehicles.
  • the system 2 may be employed to acquire images of and identify automobiles at tollway points on a roadway.

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Abstract

L'invention concerne un système de détection comprenant des détecteurs passifs (3) pour recevoir des radiations électromagnétiques d'un objet mobile (28) et générer des signaux d'intensité représentatifs de la radiation reçue et un système de traitement pour soustraire les signaux d'intensité et obtenir une signature différentielle, représentative de la position de l'objet mobile. Un système de saisie d'images comprend au moins une caméra (7) pour saisir l'image d'au moins une partie d'un objet mobile, en réponse à un signal de déclenchement, et un système d'analyse pour traiter l'image afin de localiser une région dans l'image comprenant des marques d'identification de l'objet et pour traiter la région afin d'extraire ces marques en vue d'une reconnaissance optique.
PCT/AU1997/000198 1996-03-29 1997-03-27 Systeme de detection d'avion WO1997037336A1 (fr)

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EP97913985A EP0890161A4 (fr) 1996-03-29 1997-03-27 Systeme de detection d'avion
NZ332051A NZ332051A (en) 1996-03-29 1997-03-27 Detecting position of aircraft flying overhead for accurately recording registration markings
AU21438/97A AU720315B2 (en) 1996-03-29 1997-03-27 An aircraft detection system

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AUPN9032A AUPN903296A0 (en) 1996-03-29 1996-03-29 An aircraft detection system

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EP1170715A3 (fr) * 2000-07-04 2003-01-29 H.A.N.D. GmbH Procédé de surveillance au sol
EP1187083A3 (fr) * 2000-09-08 2003-05-07 Zapfe, Hans, Dipl.-Ing.; PA Procédé et système pour surveiller les décollages et atterrissages des aéronefs
US7173526B1 (en) 2000-10-13 2007-02-06 Monroe David A Apparatus and method of collecting and distributing event data to strategic security personnel and response vehicles
US7197228B1 (en) 1998-08-28 2007-03-27 Monroe David A Multifunction remote control system for audio and video recording, capture, transmission and playback of full motion and still images
US7228429B2 (en) 2001-09-21 2007-06-05 E-Watch Multimedia network appliances for security and surveillance applications
US7365871B2 (en) 1998-01-12 2008-04-29 Monroe David A Apparatus for capturing, converting and transmitting a visual image signal via a digital transmission system
US7400249B2 (en) 2001-10-10 2008-07-15 Monroe David A Networked personal security system
US7428002B2 (en) 2002-06-05 2008-09-23 Monroe David A Emergency telephone with integrated surveillance system connectivity
US7511612B1 (en) 1999-02-25 2009-03-31 Monroe David A Ground based security surveillance system for aircraft and other commercial vehicles
US7539357B1 (en) 1997-03-14 2009-05-26 Monroe David A Method and apparatus for sending and receiving facsimile transmissions over a non-telephonic transmission system
US7576770B2 (en) 2003-02-11 2009-08-18 Raymond Metzger System for a plurality of video cameras disposed on a common network
US7634662B2 (en) 2002-11-21 2009-12-15 Monroe David A Method for incorporating facial recognition technology in a multimedia surveillance system
US7634334B2 (en) 2002-11-22 2009-12-15 Monroe David A Record and playback system for aircraft
US7640083B2 (en) 2002-11-22 2009-12-29 Monroe David A Record and playback system for aircraft
US7643168B2 (en) 2003-01-03 2010-01-05 Monroe David A Apparatus for capturing, converting and transmitting a visual image signal via a digital transmission system
CN110702723A (zh) * 2018-07-09 2020-01-17 浙江清华柔性电子技术研究院 高温风洞的成像系统和方法
US10585185B2 (en) 2017-02-03 2020-03-10 Rohde & Schwarz Gmbh & Co. Kg Security scanning system with walk-through-gate
CN111316340A (zh) * 2017-06-05 2020-06-19 Wing航空有限责任公司 跨多个服务供应者共享整个空域的无人飞行器系统数据库的方法和系统
CN113281341A (zh) * 2021-04-19 2021-08-20 唐山学院 热镀锌带钢的双传感器表面质量检测系统的检测优化方法
CN113474788A (zh) * 2019-07-23 2021-10-01 东洋制罐株式会社 影像数据处理系统、无人飞机、影像数据处理方法及非暂存计算机可读取记忆媒体
CN115656478A (zh) * 2022-11-14 2023-01-31 中国科学院、水利部成都山地灾害与环境研究所 一种模拟冰颗粒循环剪切的防渗剪切试验装置及使用方法
US12032278B2 (en) 2019-02-08 2024-07-09 Photon-X, Inc. Integrated spatial phase imaging
US12175600B2 (en) 2019-08-12 2024-12-24 Photon-X, Inc. Data management system for spatial phase imaging
US12342648B2 (en) 2019-05-17 2025-06-24 Photon-X, Inc. Spatial phase integrated wafer-level imaging

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GB2624653A (en) * 2022-11-24 2024-05-29 Continental Autonomous Mobility Germany GmbH A system and method for object detection from a curved mirror

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Cited By (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7539357B1 (en) 1997-03-14 2009-05-26 Monroe David A Method and apparatus for sending and receiving facsimile transmissions over a non-telephonic transmission system
US7365871B2 (en) 1998-01-12 2008-04-29 Monroe David A Apparatus for capturing, converting and transmitting a visual image signal via a digital transmission system
US7197228B1 (en) 1998-08-28 2007-03-27 Monroe David A Multifunction remote control system for audio and video recording, capture, transmission and playback of full motion and still images
US7359622B2 (en) 1998-08-28 2008-04-15 Monroe David A Multifunction remote control system for audio and video recording, capture, transmission and playback of full motion and still images
US7428368B1 (en) 1998-08-28 2008-09-23 Monroe David A Multifunction remote control system for audio and video recording, capture, transmission and playback of full motion and still images
US7511612B1 (en) 1999-02-25 2009-03-31 Monroe David A Ground based security surveillance system for aircraft and other commercial vehicles
US7551075B1 (en) 1999-02-25 2009-06-23 David A Monroe Ground based security surveillance system for aircraft and other commercial vehicles
EP1170715A3 (fr) * 2000-07-04 2003-01-29 H.A.N.D. GmbH Procédé de surveillance au sol
EP1187083A3 (fr) * 2000-09-08 2003-05-07 Zapfe, Hans, Dipl.-Ing.; PA Procédé et système pour surveiller les décollages et atterrissages des aéronefs
US7173526B1 (en) 2000-10-13 2007-02-06 Monroe David A Apparatus and method of collecting and distributing event data to strategic security personnel and response vehicles
US7561037B1 (en) 2000-10-13 2009-07-14 Monroe David A Apparatus for and method of collecting and distributing event data to strategic security personnel and response vehicles
US7228429B2 (en) 2001-09-21 2007-06-05 E-Watch Multimedia network appliances for security and surveillance applications
US7400249B2 (en) 2001-10-10 2008-07-15 Monroe David A Networked personal security system
US7495562B2 (en) 2001-10-10 2009-02-24 David A Monroe Networked personal security system
US7428002B2 (en) 2002-06-05 2008-09-23 Monroe David A Emergency telephone with integrated surveillance system connectivity
US7634662B2 (en) 2002-11-21 2009-12-15 Monroe David A Method for incorporating facial recognition technology in a multimedia surveillance system
US7634334B2 (en) 2002-11-22 2009-12-15 Monroe David A Record and playback system for aircraft
US7640083B2 (en) 2002-11-22 2009-12-29 Monroe David A Record and playback system for aircraft
US7643168B2 (en) 2003-01-03 2010-01-05 Monroe David A Apparatus for capturing, converting and transmitting a visual image signal via a digital transmission system
US7576770B2 (en) 2003-02-11 2009-08-18 Raymond Metzger System for a plurality of video cameras disposed on a common network
US10585185B2 (en) 2017-02-03 2020-03-10 Rohde & Schwarz Gmbh & Co. Kg Security scanning system with walk-through-gate
CN111316340B (zh) * 2017-06-05 2023-03-07 Wing航空有限责任公司 跨多个服务供应者共享整个空域的无人飞行器系统数据库的方法和系统
CN111316340A (zh) * 2017-06-05 2020-06-19 Wing航空有限责任公司 跨多个服务供应者共享整个空域的无人飞行器系统数据库的方法和系统
US11488484B2 (en) 2017-06-05 2022-11-01 Wing Aviation Llc Methods and systems for sharing an airspace wide unmanned aircraft system database across a plurality of service suppliers
CN110702723A (zh) * 2018-07-09 2020-01-17 浙江清华柔性电子技术研究院 高温风洞的成像系统和方法
US12032278B2 (en) 2019-02-08 2024-07-09 Photon-X, Inc. Integrated spatial phase imaging
US12342648B2 (en) 2019-05-17 2025-06-24 Photon-X, Inc. Spatial phase integrated wafer-level imaging
CN113474788A (zh) * 2019-07-23 2021-10-01 东洋制罐株式会社 影像数据处理系统、无人飞机、影像数据处理方法及非暂存计算机可读取记忆媒体
CN113474788B (zh) * 2019-07-23 2024-02-13 东洋制罐株式会社 影像数据处理系统、无人飞机、影像数据处理方法及非暂存计算机可读取记忆媒体
US12106447B2 (en) 2019-07-23 2024-10-01 Toyo Seikan Co., Ltd. Image data processing system, unmanned aerial vehicle, image data processing method, and non-transitory computer-readable recording medium
US12175600B2 (en) 2019-08-12 2024-12-24 Photon-X, Inc. Data management system for spatial phase imaging
CN113281341A (zh) * 2021-04-19 2021-08-20 唐山学院 热镀锌带钢的双传感器表面质量检测系统的检测优化方法
CN115656478A (zh) * 2022-11-14 2023-01-31 中国科学院、水利部成都山地灾害与环境研究所 一种模拟冰颗粒循环剪切的防渗剪切试验装置及使用方法

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ZA972699B (en) 1997-11-18
EP0890161A1 (fr) 1999-01-13
NZ332051A (en) 2000-05-26
EP0890161A4 (fr) 1999-06-16
CA2250927A1 (fr) 1997-10-09
ID17121A (id) 1997-12-04
AUPN903296A0 (en) 1996-04-26
KR20000005409A (en) 2000-01-25

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